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Clinical Corner: Through a New Lens: Use of Surveillance Data in Estimating Statewide HAI Costs

Posted on 11/06/13


Healthcare-associated infections (HAIs) lead to devastating patient morbidity and mortality and result in a substantial economic burden for the nation's healthcare system. In light of the impact on patient safety and attributable costs, the US Department of Health and Human Services developed an Action Plan for HAI reduction and a foundation to focus national attention on improving healthcare quality.

In 2009, federal funding was allocated to state health departments to implement the HHS Action Plan. In order to receive funding, a statewide HAI prevention plan was required. A challenging aspect of such large scale planning efforts is developing a statewide process and outcome metrics. Quantifying HAI attributable costs can serve as a useful guide to focus HAI prevention efforts and choose appropriate metrics.

Dr. Deverick Anderson et. al. developed a novel approach by using statewide infection surveillance data to assess economic impact and provide estimates for the direct attributable costs of HAIs. The group sent surveys to 117 acute care North Carolina hospitals to collect hospital-specific surveillance denominator data, number and type of critical care units, and number of infection preventionists on staff.

This data was averaged to define a "standard" NC acute care hospital: A "standard" NC hospital diagnosed approximately 100 HAI each year with estimated costs of $985,000 to $2.7 million. The most common HAI was SSI (73%). Costs related to SSI accounted for 87% to 91% of overall costs.

These findings support the fascinating shift from UTI to SSI as the most common healthcare-associated infection. It also seems to suggest that CMS surgical site infection reporting of colon and abdominal hysterectomy procedures may only be the tip of the iceberg.

Where do you think the next new focus on HAI reporting should be placed?

Data published by the National Healthcare Safety Network (NHSN) provided mean hospital rates for the HAI infection types included in the study. HAI minimum and maximum cost estimates were then leveraged based upon published data from the Centers for Disease Control and Prevention.

A few considerations in deciding whether this approach is right for your state:

  1. Comfort level with the assumptions outlined in the aforementioned research.
    • All hospitals assumed to have rates equal to NHSN means.
    • Hospitals assumed to have the same HAI rate by standardization.
    • Costs assumed to be equal across all hospitals.
  2. Are the Infection Preventionists within hospitals across your state collecting denominator data in the same manner? Variations in practice could impact the profile of your state's "standard" hospital. Although, in my estimation, these variations are unlikely to produce a statistically significant difference in the cost findings.

The research from Dr. Anderson et. al. clearly illustrates an easily reproducible method for estimating statewide costs attributable to HAIs. This approach may help other states in planning and resourcing regarding potential investments in HAI prevention.

1. Anderson DJ, et. al. Statewide costs of health care-associated infections: Estimates for acute care hospitals in North Carolina. Am J Infect Control 2013;41:764-768. 

2. Scott RD. The direct medical costs of healthcare-associated infection in US hospitals and the benefits of prevention. Atlanta [GA]: Division of Healthcare Quality Promotion. Centers for Disease Control and Prevention; 2009. 

3. Edwards JR, Peterson KD, Mu Y, Banerjee S, Allen-Bridson K, Morrell G, et. al. National Healthcare Safety Network (NHSN) report: data summary for 2006-2008, issued December 2009. Am J Infect Control 2009;37:783-805.

Implementation of Risk Evaluation and Mitigation Strategy Programs in a Health System

Topics: Infection Prevention

About the Author

Matthew Weissenbach, MPH, CPH, CIC is the Director of Clinical Operations for Pharmacy OneSource. As a trained epidemiologist, Matt has significant experience within the healthcare informatics arena centered on leveraging automation to advance the fields of epidemiology and infection prevention. He has also been extensively involved in international public health, specifically infectious disease epidemiology and vector-borne diseases endemic to Southeast Asia. Matt is a member of the Association for Professionals in Infection Control and Epidemiology (APIC) at the national and local (NC) levels as well as a member of the Society for Healthcare Epidemiology of America (SHEA). Matt received his Master of Public Health degree in Global Health Practice from the University of South Florida and is board certified in Public Health and Infection Control.